52 citations · 57 across the 4 of their papers we have counts for
11 papers
Reassignment of magic numbers for icosahedral Au clusters: 310, 564, 928 and 1426
Jan Kloppenburg, Andreas Pedersen, Kari Laasonen +2
Icosahedral Au clusters with three and four shells of atoms are found to deviate significantly from the commonly assumed Mackay structures. By introducing additional atoms in the s…
Machine learning force fields based on local parametrization of dispersion interactions: Application to the phase diagram of C
Heikki Muhli, Xi Chen, Albert P. Bartók +4
We present a comprehensive methodology to enable addition of van der Waals (vdW) corrections to machine learning (ML) atomistic force fields. Using a Gaussian approximation potenti…
Particle Swarm Based Hyper-Parameter Optimization for Machine Learned Interatomic Potentials
Suresh Kondati Natarajan, Miguel A. Caro
Modeling non-empirical and highly flexible interatomic potential energy surfaces (PES) using machine learning (ML) approaches is becoming popular in molecular and materials researc…
Machine learning driven simulated deposition of carbon films: from low-density to diamondlike amorphous carbon
Miguel A. Caro, Gábor Csányi, Tomi Laurila +1
Amorphous carbon (a-C) materials have diverse interesting and useful properties, but the understanding of their atomic-scale structures is still incomplete. Here, we report on exte…
Fully analytic valence force field model for the elastic and inner elastic properties of diamond and zincblende crystals
Daniel S. P. Tanner, Miguel A. Caro, Stefan Schulz +1
Using a valence force field model based on that introduced by Martin, we present three related methods through which we analytically determine valence force field parameters. The m…
Towards the computational experiment
Miguel A. Caro
We give a brief account of the current limitations and possibilities in the field of computational simulation of materials. We then focus on the effect that the emergence of machin…